Abstract
A fast iterative solving method of various types of fuzzy relational equations is proposed. This method is derived by eliminating a redundant comparison process in the conventional iterative solving method (Pedrycz, 1983). The proposed method is applied to image reconstruction, and confirmed that the computation time is decreased to 1/39 - 1/45 with the compression rate of 0.0625. Furthermore, in order to make any initial solution converge on a reconstructed image with good quality, a new cost function is proposed. Under the condition that the compression rate is 0.0625, it is confirmed that the root mean square error of the proposed method decreases to 24.00% and 86.03% compared with those of the conventional iterative method and a non iterative image reconstruction method (Nobuhara, 2001), respectively.
| Original language | English |
|---|---|
| Pages (from-to) | 90-98 |
| Number of pages | 9 |
| Journal | Journal of Advanced Computational Intelligence and Intelligent Informatics |
| Volume | 5 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Mar 2001 |
| Externally published | Yes |
Keywords
- Fuzzy relational equation
- Gradient method
- Image compression
- Optimization